Prostate cancer is the most common cancer and the second leading cause of cancer deaths among men in the U.S. Epidemiological data and segregation analyses support the hypothesis that genetic components contribute strongly to susceptibility, particularly in men diagnosed at younger ages or men with a family history of disease. We have conducted a genome-wide scan of 254 high-risk prostate cancer families collected, characterized, and genotyped largely in the past 3 years. We now propose to utilize the resulting data to identify putative susceptibility genes through the following aims. Initially, we will assign priorities for follow-up of provocative regions by refined mapping. Analyses derived from the entire data set as well as stratified subsets of families grouped by age at onset, family history, and clinical features of disease will be considered. Regions for which the most compelling and consistent data are observed using a set of stated criteria will be selected for detailed follow-up and verification. Once loci of interest are prioritized, we will define a minimum critical region for each by genotyping additional markers and identifying recombinants relative to markers and known genes. A physical map of BACs across regions of interest will be constructed using publicly available data, with gaps filled In by additional screening and sequencing as needed. Oligoarrays of exons across the minimum region will then be constructed and probed with mRNA isolated from both normal prostate and tumor to identify genes from the region of interest. Additional information will likely be derived from analysis of tumors from putatively linked families on the same oligoarrays. Final selection of candidate genes will be made using array data, functional information, and publicly available expression data. Full-length cDNA clones will be isolated and sequenced as needed. These genes, together with any identified by other investigators, will be fully analyzed for disease-associated mutations and polymorphisms, including SNPs, in the 254 family data set. The resulting data will provide information about the type and distribution of mutations in high-risk families as well as provide useful information for understanding genetic heterogeneity of prostate cancer.
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